Recommendation systems can enhance the selection process for users. For media segments, recommendations are available to provide recommendations for various media including video, audio, books, software, images, papers, etc. Recommendation systems may be based on research models or based upon collaborative filtering. Some systems create special rules and combine one or more recommendation philosophies in generating suggestions for users. Conventional models of recommendation usually function based on the past behavior of the user which is provided to the recommendation system to generate recommendations. Past behavior can include browsing a music website, music downloaded via a music service, etc. In general, the more data that is available, the better the recommendation system can identify a user's likes and dislikes.